Support weighted losses

model.py

@@ -168,14 +168,18 @@ class StaticGraphAdapter(object):
             label_vars = []
             if self.mode != 'test':
                 losses = []
-                for o, l in zip(outputs, self.model._loss_functions):
+                loss_weights = self.model._loss_weights
+                if loss_weights is None:
+                    loss_weights = [1. for _ in self.model._loss_functions]
+                for o, l, w in zip(outputs, self.model._loss_functions,
+                                   loss_weights):
                     if l is None:
                         continue
                     label_var = self._infer_label_var(o, l)
                     label_vars.append(label_var)
                     loss_fn = getattr(fluid.layers, l)
                     loss = loss_fn(o, label_var)
-                    losses.append(fluid.layers.reduce_mean(loss))
+                    losses.append(fluid.layers.reduce_mean(loss) * w)
                 outputs = losses
                 if self.mode == 'train':
                     self._label_vars = label_vars
@@ -314,12 +318,16 @@ class DynamicGraphAdapter(object):
 
     def _loss(self, pred, labels):
         losses = []
-        for o, l, t in zip(to_list(pred), self.model._loss_functions, labels):
+        loss_weights = self.model._loss_weights
+        if loss_weights is None:
+            loss_weights = [1. for _ in self.model._loss_functions]
+        for o, l, w, t in zip(to_list(pred), self.model._loss_functions,
+                              loss_weights, labels):
             if l is None:
                 continue
             loss_fn = getattr(fluid.layers, l)
             loss = loss_fn(o, to_variable(t))
-            losses.append(fluid.layers.reduce_mean(loss))
+            losses.append(fluid.layers.reduce_mean(loss) * w)
         return losses
 
 
@@ -328,6 +336,7 @@ class Model(fluid.dygraph.Layer):
         super(Model, self).__init__(self.__class__.__name__)
         self.mode = 'train'
         self._loss_functions = []
+        self._loss_weights = None
         self._optimizer = None
         if in_dygraph_mode():
             self._adapter = DynamicGraphAdapter(self)
@@ -349,9 +358,11 @@ class Model(fluid.dygraph.Layer):
     def load(self, *args, **kwargs):
         return self._adapter.load(*args, **kwargs)
 
-    def prepare(self, optimizer, loss_functions):
+    def prepare(self, optimizer, loss_functions, loss_weights=None):
         self._optimizer = optimizer
         self._loss_functions = to_list(loss_functions)
+        if loss_weights is not None:
+            self._loss_weights = to_list(loss_weights)
 
     def parameters(self, *args, **kwargs):
         return self._adapter.parameters(*args, **kwargs)